no code implementations • 24 Jan 2024 • Xia Chen, Alexander Rex, Janis Woelke, Christoph Eckert, Boris Bensmann, Richard Hanke-Rauschenbach, Philipp Geyer
In this study, we propose to adopt a novel framework, Knowledge-integrated Machine Learning, for advancing Proton Exchange Membrane Water Electrolysis (PEMWE) development.
no code implementations • 11 Sep 2023 • Xia Chen, Ruiji Sun, Ueli Saluz, Stefano Schiavon, Philipp Geyer
The decision-making process in real-world implementations has been affected by a growing reliance on data-driven models.
no code implementations • 10 Jul 2023 • Xia Chen, Philipp Geyer
Despite the digitalization trend and data volume surge, first-principles models (also known as logic-driven, physics-based, rule-based, or knowledge-based models) and data-driven approaches have existed in parallel, mirroring the ongoing AI debate on symbolism versus connectionism.
no code implementations • 19 Apr 2023 • Zihao Huang, Yue Wang, Weixing Xin, Xingtong Lin, Huizhen Li, Haowen Chen, Yizhen Lao, Xia Chen
Aiming at the problem of few-shot samples, a Siamese neural network suitable for classification model is proposed.
no code implementations • 23 Jan 2023 • Xia Chen, Manav Mahan Singh, Philipp Geyer
In this study, component-based machine learning (CBML) as the knowledge-encoded data-driven method is examined in the context of energy-efficient building engineering.
1 code implementation • 23 Jan 2023 • Xia Chen, Xiaoye Cai, Alexander Kümpel, Dirk Müller, Philipp Geyer
The framework is integrated with a feedforward loop that embedded a dynamic building environment with leading and lagging system information involved: The simulation combined with system characteristic information is imported to the ML predictive algorithms.
no code implementations • 21 Sep 2022 • Huanhai Xin, Chenxi Liu, Xia Chen, Yuxuan Wang, Eduardo Prieto-Araujo, Linbin Huang
Based on our analysis, we further study the problem of how to configure GFM converters in the grid and how many GFM converters we will need.
1 code implementation • 15 Jul 2022 • Xia Chen, Xiangbin Teng, Han Chen, Yafeng Pan, Philipp Geyer
This study examines the efficacy of various neural network (NN) models in interpreting mental constructs via electroencephalogram (EEG) signals.
no code implementations • 19 Apr 2022 • Xia Chen, Guanlan Zhang, Michael Yu Wang, Hongyu Yu
Vision-based tactile sensors have been widely studied in the robotics field for high spatial resolution and compatibility with machine learning algorithms.
no code implementations • 30 Aug 2021 • Philipp Geyer, Manav Mahan Singh, Xia Chen
The, approach adapts the model structure to engineering methods of, systems engineering and to domain knowledge.
no code implementations • 17 Dec 2020 • Xia Chen, Jianren Wang, David Held, Martial Hebert
Visual data in autonomous driving perception, such as camera image and LiDAR point cloud, can be interpreted as a mixture of two aspects: semantic feature and geometric structure.
no code implementations • 1 Aug 2020 • Xia Chen, Jianren Wang, Martial Hebert
We propose a simple, fast, and flexible framework to generate simultaneously semantic and instance masks for panoptic segmentation.
no code implementations • 14 May 2019 • Xia Chen, Guoxian Yu, Jun Wang, Carlotta Domeniconi, Zhao Li, Xiangliang Zhang
To maximize the profit of utilizing the rare and valuable supervised information in HNEs, we develop a novel Active Heterogeneous Network Embedding (ActiveHNE) framework, which includes two components: Discriminative Heterogeneous Network Embedding (DHNE) and Active Query in Heterogeneous Networks (AQHN).
no code implementations • 5 Apr 2019 • Jianren Wang, Yihui He, Xiaobo Wang, Xinjia Yu, Xia Chen
We introduce a prediction driven method for visual tracking and segmentation in videos.